This Jupyter Notebook provides an exploratory data analysis (EDA) of a dataset named data.csv, which likely contains information related to chat interactions. The analysis includes statistical summaries, visualizations, and initial insights to better understand the structure and characteristics of the chat data.
📦ChatBot Interaction.ipynb
└── 📄 data.csv (not provided in this repo)
- Data loading using
pandas - Summary statistics and data types overview
- Visual analysis using
seabornandmatplotlib - Structure inspection (
df.head(),df.describe(),df.info())
- Python 3.x
- pandas
- numpy
- seaborn
- matplotlib
To perform a preliminary analysis of chat-based data and uncover basic statistical properties and potential patterns that may help guide further machine learning or natural language processing (NLP) tasks.
- Clone the repository or download the notebook.
- Ensure
data.csvis available in the same directory as the notebook. - Install required libraries:
pip install pandas numpy matplotlib seaborn
- Run the Jupyter notebook.
- The dataset (
data.csv) must be available locally for the notebook to execute. - This notebook is suitable as a foundation for more advanced chatbot or NLP pipeline development.
For questions or collaborations, feel free to reach out to:
Author: Peter Gatitu Email: petergatitu61@gmail.com